Computed tomography (CT) systems and methods are widely used, particularly for medical imaging and diagnosis. CT systems generally create images of one or more sectional slices through a subject's body. A radiation source, such as an X-ray tube, irradiates the body from one side. A collimator can limit the angular extent of the X-ray beam, so that radiation impinging on the body is substantially confined to a planar region defining a cross-sectional slice of the body. At least one detector on the opposite side of the body receives radiation transmitted through the body substantially in the plane of the slice. The attenuation of the radiation that has passed through the body is measured by processing electrical signals received from the detector.
A CT sinogram indicates attenuation through the body as a function of “space” along a detector array and “time/angle” of a scan of measurements performed at a series of projection angles. The space dimension refers to the position along a one-dimensional array of X-ray detectors. The time/angle dimension refers to the projection angle of X-rays changing as a function of time, such that as time progresses the projection angle increments and projection measurements are performed at a linear succession of projection angles. The attenuation resulting from a particular volume (e.g., a vertebra) will trace out a sine wave around the vertical axis—volumes farther from the axis of rotation having sine waves with larger amplitudes, the phase of a sine wave determining the volume's angular position around the rotation axis. Performing an inverse Radon transform or equivalent image reconstruction method reconstructs an image from the projection data in the sinogram—the reconstructed image corresponding to a cross-sectional slice of the body.
Conventionally, energy-integrating detectors have been used to measure CT projection data. Now, recent technological developments are making photon-counting detectors a feasible alternative to conventional energy-integrating detectors. Photon-counting detectors have many advantages, including their capacity for performing spectral CT. To obtain the spectral nature of the transmitted X-ray data, the photon-counting detectors split the X-ray beam into its component energies or spectrum bins and count a number of photons in each of the bins. Since spectral CT involves the detection of transmitted X-rays at two or more energy levels, spectral CT generally includes dual-energy CT by definition. Due to different materials exhibiting different spectral attenuation of the X-rays, projection data from spectral CT can be decomposed into material components using a material decomposition. The material-component images can then be reconstructed from material-component sinograms.
One result of this material decomposition of spectrally resolved projection data is that strong noise correlations are introduced among the material-component sinograms and material-component images. The correlations of the noise can be used to denoise in order to improve image quality of the reconstructed images. Denoising reconstructed material images is desirable to enhance the diagnostic quality of these images. Conventional methods of denoising material-component images either are computationally intensive or do not utilize the correlated nature of the noise to improve denoising.